Left atrial appendage occlusion in patients suffering from advanced chronic kidney disease (stage 4 and 5). Long-term follow-up.

INTRODUCTION AND OBJECTIVES: Advanced chronic kidney disease (A-CKD) combined with atrial fibrillation increases the risk of both thrombogenic and bleeding events. Left atrial appendage occlusion (LAAO) may be an alternative to oral anticoagulation to prevent thromboembolic events. We aimed to evaluate the outcomes of LAAO in patients with A-CKD. METHODS: Comparison at long-term follow-up of patients diagnosed with and without A-CKD (eGFR<30 mL/min/1.73 m2 ) who underwent LAAO between 2009 and May 2022. RESULTS: Five hundred seventy-three patients were included. Eighty-one (14%) were diagnosed with A-CKD. There were no differences in sex, age, and cardiovascular risk factors, except for diabetes which was more frequent in patients with A-CKD. The control group had higher rates of stroke, both ischemic and hemorrhagic. There were no differences in the CHA2 DS2 -VASc score, although A-CKD patients had a higher bleeding risk according to the HASBLED scale. Global procedural success was 99.1%. At follow-up, there were no differences in stroke rate: at 1-year (HR: 1.22, IC-95%: 0.14-10.42, p = 0.861); at 5-years (HR: 0.60, IC-95%: 0.08-4.58, p = 0.594). Although bleeding events were higher in the A-CKD group, no differences were found in major bleeding (defined BARC ≥ 3) at 1-year (HR: 1.34, IC-95%: 0.63-2.88, p = 0.464) or at 5-years follow-up (HR: 1.30, IC-95%: 0.69-2.48, p = 0.434). Mortality rate at 5 years was higher in the A-CKD patients (HR: 1.84, IC-95%: 1.18-2.87, p = 0.012). CONCLUSIONS: LAAO is an effective and safe treatment in A-CKD patients to prevent ischemic events and bleeding. This strategy could be an alternative to oral anticoagulation in this high-risk group of patients.

Sodium-glucose cotransporter 2 inhibition in primary and secondary glomerulonephritis.

BACKGROUND: The role of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in the management glomerular/systemic autoimmune diseases with proteinuria in real-world clinical settings is unclear. METHODS: This is a retrospective, observational, international cohort study. Adult patients with biopsy-proven glomerular diseases were included. The main outcome was the percentage reduction in 24-h proteinuria from SGLT2i initiation to 3, 6, 9 and 12 months. Secondary outcomes included percentage change in estimated glomerular filtration rate (eGFR), proteinuria reduction by type of disease and reduction of proteinuria ≥30% from SGLT2i initiation. RESULTS: Four-hundred and ninety-three patients with a median age of 55 years and background therapy with renin-angiotensin system blockers were included. Proteinuria from baseline changed by -35%, -41%, -45% and -48% at 3, 6, 9 and 12 months after SGLT2i initiation, while eGFR changed by -6%, -3%, -8% and -10.5% at 3, 6, 9 and 12 months, respectively. Results were similar irrespective of the underlying disease. A correlation was found between body mass index (BMI) and percentage proteinuria reduction at last follow-up. By mixed-effects logistic regression model, serum albumin at SGLT2i initiation emerged as a predictor of ≥30% proteinuria reduction (odds ratio for albumin <3.5 g/dL, 0.53; 95% CI 0.30-0.91; P = .02). A slower eGFR decline was observed in patients achieving a ≥30% proteinuria reduction: -3.7 versus -5.3 mL/min/1.73 m2/year (P = .001). The overall tolerance to SGLT2i was good. CONCLUSIONS: The use of SGLT2i was associated with a significant reduction of proteinuria. This percentage change is greater in patients with higher BMI. Higher serum albumin at SGLT2i onset is associated with higher probability of achieving a ≥30% proteinuria reduction.

Comparison of antipsychotic drug use in children and adolescents in the Netherlands before and during the COVID-19 pandemic.

This study aims to describe the patterns and trends in antipsychotic prescription among Dutch youth before and during the corona virus disease 2019 (COVID-19) pandemic (between 2017 and 2022). The study specifically aims to determine whether there has been an increase or decrease in antipsychotic prescription among this population, and whether there are any differences in prescription patterns among different age and sex groups. The study utilized the IADB database, which is a pharmacy prescription database containing dispensing data from approximately 120 community pharmacies in the Netherlands, to analyze the monthly prevalence and incidence rates of antipsychotic prescription among Dutch youth before and during the pandemic. The study also examined the prescribing patterns of the five most commonly used antipsychotics and conducted an autoregressive integrated moving average (ARIMA) analysis using data prior to the pandemic, to predict the expected prevalence rate during the pandemic. The prescription rate of antipsychotics for Dutch youth was slightly affected by the pandemic, with a monthly prevalence of 4.56 [4.50-4.62] per 1000 youths before COVID-19 pandemic and 4.64 [4.59-4.69] during the pandemic. A significant increase in prevalence was observed among adolescent girls aged 13-19 years. The monthly incidence rate remained stable overall, but rose for adolescent girls aged 13-19 years. Aripiprazole, and Quetiapine had higher monthly prevalence rates during the pandemic, while Risperidone and Pipamperon had lower rates. Similarly, the monthly incidence rates of Aripiprazole and Olanzapine went up, while Risperidone went down. Furthermore, the results from the ARIMA analysis revealed that despite the pandemic, the monthly prevalence rate of antipsychotic prescription was within expectation. The findings of this study suggest that there has been a moderate increase in antipsychotic prescription among Dutch youth during the COVID-19 pandemic, particularly in adolescent females aged 13-19 years. However, the study also suggests that factors beyond the pandemic may be contributing to the rise in antipsychotic prescription in Dutch youth.

Nudging intensive care unit personnel towards sustainable behaviour.

BACKGROUND: The health care sector is among the most carbon-intensive sectors, contributing to societal problems like climate change. Previous research demonstrated that especially the use of personal protective equipment (e.g., aprons) in critical care contributes to this problem. To reduce personal protective equipment waste, new sustainable policies are needed. AIMS: Policies are only effective if people comply. Our aim is to examine whether compliance with sustainable policies in critical care can be increased through behavioural influencing. Specifically, we examined the effectiveness of two sets of nudges (i.e., a Prime + Visual prompt nudge and a Social norm nudge) on decreasing apron usage in an intensive care unit (ICU). STUDY DESIGN: We conducted a field experiment with a pre- and post-intervention measurement. Upon the introduction of the new sustainable policy, apron usage data were collected for 9 days before (132 observations) and 9 days after (114 observations) the nudge interventions were implemented. RESULTS: Neither the Prime + Visual prompt nudge, nor the Social norm nudge decreased apron usage. CONCLUSIONS: While previous studies have found that primes, visual nudges and social norm nudges can increase sustainable behaviour, we did not find evidence for this in our ICU field experiment. Future research is needed to determine whether this null finding reflects reality, or whether it was due to methodological decisions and limitations of the presented experiment. RELEVANCE TO CLINICAL PRACTICE: The presented study highlights the importance of studying behavioural interventions that were previously proven successful in the lab and in other field contexts, in the complex setting of critical care. Results previously found in other contexts may not generalize directly to a critical care context. The unique characteristics of the critical care context also pose methodological challenges that may have affected the outcomes of this experiment.

Disrupted relationship between intrinsic neural timescales and alpha peak frequency during unconscious states - A high-density EEG study.

Our brain processes the different timescales of our environment's temporal input stochastics. Is such a temporal input processing mechanism key for consciousness? To address this research question, we calculated measures of input processing on shorter (alpha peak frequency, APF) and longer (autocorrelation window, ACW) timescales on resting-state high-density EEG (256 channels) recordings and compared them across different consciousness levels (awake/conscious, ketamine and sevoflurane anaesthesia, unresponsive wakefulness, minimally conscious state). We replicate and extend previous findings of: (i) significantly longer ACW values, consistently over all states of unconsciousness, as measured with ACW-0 (an unprecedented longer version of the well-know ACW-50); (ii) significantly slower APF values, as measured with frequency sliding, in all four unconscious states. Most importantly, we report a highly significant correlation of ACW-0 and APF in the conscious state, while their relationship is disrupted in the unconscious states. In sum, we demonstrate the relevance of the brain's capacity for input processing on shorter (APF) and longer (ACW) timescales - including their relationship - for consciousness. Albeit indirectly, e.g., through the analysis of electrophysiological activity at rest, this supports the mechanism of temporo-spatial alignment to the environment's temporal input stochastics, through relating different neural timescales, as one key predisposing factor of consciousness.

Intrinsic dynamics and topography of sensory input systems.

The brain is continuously bombarded by external stimuli, which are processed in different input systems. The intrinsic features of these sensory input systems remain yet unclear. Investigating topography and dynamics of input systems is the goal of our study in order to better understand the intrinsic features that shape their neural processing. Using a functional magnetic resonance imaging dataset, we measured neural topography and dynamics of the input systems during rest and task states. Neural dynamics were probed by scale-free activity, measured with the power-law exponent (PLE), as well as by order/disorder as measured with sample entropy (SampEn). Our main findings during both rest and task states are: 1) differences in neural dynamics (PLE, SampEn) between regions within each of the three sensory input systems 2) differences in topography and dynamics among the three input systems; 3) PLE and SampEn correlate and, as demonstrated in simulation, show non-linear relationship in the critical range of PLE; 4) scale-free activity during rest mediates the transition of SampEn from rest to task as probed in a mediation model. We conclude that the sensory input systems are characterized by their intrinsic topographic and dynamic organization which, through scale-free activity, modulates their input processing.

It's in the Timing: Reduced Temporal Precision in Neural Activity of Schizophrenia.

Studies of perception and cognition in schizophrenia (SCZ) show neuronal background noise (ongoing activity) to intermittently overwhelm the processing of external stimuli. This increased noise, relative to the activity evoked by the stimulus, results in temporal imprecision and higher variability of behavioral responses. What, however, are the neural correlates of temporal imprecision in SCZ behavior? We first report a decrease in electroencephalography signal-to-noise ratio (SNR) in two SCZ datasets and tasks in the broadband (1-80 Hz), theta (4-8 Hz), and alpha (8-13 Hz) bands. SCZ participants also show lower inter-trial phase coherence (ITPC)-consistency over trials in the phase of the signal-in theta. From these ITPC results, we varied phase offsets in a computational simulation, which illustrated phase-based temporal desynchronization. This modeling also provided a necessary link to our results and showed decreased neural synchrony in SCZ in both datasets and tasks when compared with healthy controls. Finally, we showed that reduced SNR and ITPC are related and showed a relationship to temporal precision on the behavioral level, namely reaction times. In conclusion, we demonstrate how temporal imprecision in SCZ neural activity-reduced relative signal strength and phase coherence-mediates temporal imprecision on the behavioral level.

From temporal to spatial topography: hierarchy of neural dynamics in higher- and lower-order networks shapes their complexity.

The brain shows a topographical hierarchy along the lines of lower- and higher-order networks. The exact temporal dynamics characterization of this lower-higher-order topography at rest and its impact on task states remains unclear, though. Using 2 functional magnetic resonance imaging data sets, we investigate lower- and higher-order networks in terms of the signal compressibility, operationalized by Lempel-Ziv complexity (LZC). As we assume that this degree of complexity is related to the slow-fast frequency balance, we also compute the median frequency (MF), an estimation of frequency distribution. We demonstrate (i) topographical differences at rest between higher- and lower-order networks, showing lower LZC and MF in the former; (ii) task-related and task-specific changes in LZC and MF in both lower- and higher-order networks; (iii) hierarchical relationship between LZC and MF, as MF at rest correlates with LZC rest-task change along the lines of lower- and higher-order networks; and (iv) causal and nonlinear relation between LZC at rest and LZC during task, with MF at rest acting as mediator. Together, results show that the topographical hierarchy of lower- and higher-order networks converges with their temporal hierarchy, with these neural dynamics at rest shaping their range of complexity during task states in a nonlinear way.

Variability and task-responsiveness of electrophysiological dynamics: Scale-free stability and oscillatory flexibility.

Cortical oscillations and scale-free neural activity are thought to influence a variety of cognitive functions, but their differential relationships to neural stability and flexibility has never been investigated. Based on the existing literature, we hypothesize that scale-free and oscillatory processes in the brain exhibit different trade-offs between stability and flexibility; specifically, cortical oscillations may reflect variable, task-responsive aspects of brain activity, while scale-free activity is proposed to reflect a more stable and task-unresponsive aspect. We test this hypothesis using data from two large-scale MEG studies (HCP: n = 89; CamCAN: n = 195), operationalizing stability and flexibility by task-responsiveness and spontaneous intra-subject variability in resting state. We demonstrate that the power-law exponent of scale-free activity is a highly stable parameter, which responds little to external cognitive demands and shows minimal spontaneous fluctuations over time. In contrast, oscillatory power, particularly in the alpha range (8-13 Hz), responds strongly to tasks and exhibits comparatively large spontaneous fluctuations over time. In sum, our data support differential roles for oscillatory and scale-free activity in the brain with respect to neural stability and flexibility. This result carries implications for criticality-based theories of scale-free activity, state-trait models of variability, and homeostatic views of the brain with regulated variables vs. effectors.

Expression of the K74 Killer Toxin from Saccharomyces paradoxus Is Modulated by the Toxin-Encoding M74 Double-Stranded RNA 5' Untranslated Terminal Region.

Yeast killer toxins are widely distributed in nature, conferring a competitive advantage to the producer yeasts over nonkiller ones when nutrients are scarce. Most of these toxins are encoded on double-stranded RNAs (dsRNAs) generically called M. L-A members of the viral family Totiviridae act as helper viruses to maintain M, providing the virion proteins that separately encapsidate and replicate L-A and M genomes. M genomes are organized in three regions, a 5' region coding the preprotoxin, followed by an internal poly(A) stretch and a 3' noncoding region. In this work, we report the characterization of K74 toxin encoded on M74 dsRNA from Saccharomyces paradoxus Q74.4. In M74, there is a 5' upstream sequence of 141 nucleotides (nt), which contains regulatory signals for internal translation of the preprotoxin open reading frame (ORF) at the second AUG codon. The first AUG close to the 5' end is not functional. For K74 analysis, M74 viruses were first introduced into laboratory strains of Saccharomyces cerevisiae. We show here that the mature toxin is an α/ß heterodimer linked by disulfide bonds. Though the toxin (or preprotoxin) confers immunity to the carrier, cells with increased K74 loads have a sick phenotype that may lead to cell death. Thus, a fine-tuning of K74 production by the upstream regulatory sequence is essential for the host cell to benefit from the toxin it produces and, at the same time, to safely avoid damage by an excess of toxin. IMPORTANCE Killer yeasts produce toxins to which they are immune by mechanisms not well understood. This self-immunity, however, is compromised in certain strains, which secrete an excess of toxin, leading to sick cells or suicidal phenotypes. Thus, a fine-tuning of toxin production has to be achieved to reach a balance between the beneficial effect of toxin production and the stress imposed on the host metabolism. K74 toxin from S. paradoxus is very active against Saccharomyces uvarum, among other yeasts, but an excess of toxin production is deleterious for the host. Here, we report that the presence of a 5' 141-nt upstream sequence downregulates K74 toxin precursor translation, decreasing toxin levels 3- to 5-fold. Thus, this is a special case of translation regulation performed by sequences on the M74 genome itself, which have been presumably incorporated into the viral RNA during evolution for that purpose.

Covering the Gap Between Sleep and Cognition - Mechanisms and Clinical Examples.

A growing number of studies have shown the strong relationship between sleep and different cognitive processes, especially those that involve memory consolidation. Traditionally, these processes were attributed to mechanisms related to the macroarchitecture of sleep, as sleep cycles or the duration of specific stages, such as the REM stage. More recently, the relationship between different cognitive traits and specific waves (sleep spindles or slow oscillations) has been studied. We here present the most important physiological processes induced by sleep, with particular focus on brain electrophysiology. In addition, recent and classical literature were reviewed to cover the gap between sleep and cognition, while illustrating this relationship by means of clinical examples. Finally, we propose that future studies may focus not only on analyzing specific waves, but also on the relationship between their characteristics as potential biomarkers for multiple diseases.

Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea.

The overnight polysomnography shows a range of drawbacks to diagnose obstructive sleep apnea (OSA) that have led to the search for artificial intelligence-based alternatives. Many classic machine learning methods have been already evaluated for this purpose. In this chapter, we show the main approaches found in the scientific literature along with the most used data to develop the models, useful and large easily available databases, and suitable methods to assess performances. In addition, a range of results from selected studies are presented as examples of these methods. Very high diagnostic performances are reported in these results regardless of the approaches taken. This leads us to conclude that conventional machine learning methods are useful techniques to develop new OSA diagnosis simplification proposals and to act as benchmark for other more recent methods such as deep learning.

Surface Motility Regulation of Sinorhizobium fredii HH103 by Plant Flavonoids and the NodD1, TtsI, NolR, and MucR1 Symbiotic Bacterial Regulators.

Bacteria can spread on surfaces to colonize new environments and access more resources. Rhizobia, a group of α- and ß-Proteobacteria, establish nitrogen-fixing symbioses with legumes that rely on a complex signal interchange between the partners. Flavonoids exuded by plant roots and the bacterial transcriptional activator NodD control the transcription of different rhizobial genes (the so-called nod regulon) and, together with additional bacterial regulatory proteins (such as TtsI, MucR or NolR), influence the production of different rhizobial molecular signals. In Sinorhizobium fredii HH103, flavonoids and NodD have a negative effect on exopolysaccharide production and biofilm production. Since biofilm formation and motility are often inversely regulated, we have analysed whether flavonoids may influence the translocation of S. fredii HH103 on surfaces. We show that the presence of nod gene-inducing flavonoids does not affect swimming but promotes a mode of surface translocation, which involves both flagella-dependent and -independent mechanisms. This surface motility is regulated in a flavonoid-NodD1-TtsI-dependent manner, relies on the assembly of the symbiotic type 3 secretion system (T3SS), and involves the participation of additional modulators of the nod regulon (NolR and MucR1). To our knowledge, this is the first evidence indicating the participation of T3SS in surface motility in a plant-interacting bacterium. Interestingly, flavonoids acting as nod-gene inducers also participate in the inverse regulation of surface motility and biofilm formation, which could contribute to a more efficient plant colonisation.

Lemmel's syndrome: an uncommon complication of periampullary duodenal diverticulum.

Lemmel's syndrome is an uncommon entity that causes obstructive jaundice due to a periampullary duodenal diverticulum in the absence of choledolithiasis or neoplasia. To date, there are few published cases and the etiopathogenesis remains unclear.

Headache-related circuits and high frequencies evaluated by EEG, MRI, PET as potential biomarkers to differentiate chronic and episodic migraine: Evidence from a systematic review.

BACKGROUND: The diagnosis of migraine is mainly clinical and self-reported, which makes additional examinations unnecessary in most cases. Migraine can be subtyped into chronic (CM) and episodic (EM). Despite the very high prevalence of migraine, there are no evidence-based guidelines for differentiating between these subtypes other than the number of days of migraine headache per month. Thus, we consider it timely to perform a systematic review to search for physiological evidence from functional activity (as opposed to anatomical structure) for the differentiation between CM and EM, as well as potential functional biomarkers. For this purpose, Web of Science (WoS), Scopus, and PubMed databases were screened. FINDINGS: Among the 24 studies included in this review, most of them (22) reported statistically significant differences between the groups of CM and EM. This finding is consistent regardless of brain activity acquisition modality, ictal stage, and recording condition for a wide variety of analyses. That speaks for a supramodal and domain-general differences between CM and EM that goes beyond a differentiation based on the days of migraine per month. Together, the reviewed studies demonstrates that electro- and magneto-physiological brain activity (M/EEG), as well as neurovascular and metabolic recordings from functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), show characteristic patterns that allow to differentiate between CM and EM groups. CONCLUSIONS: Although a clear brain activity-based biomarker has not yet been identified to distinguish these subtypes of migraine, research is approaching headache specialists to a migraine diagnosis based not only on symptoms and signs reported by patients. Future studies based on M/EEG should pay special attention to the brain activity in medium and fast frequency bands, mainly the beta band. On the other hand, fMRI and PET studies should focus on neural circuits and regions related to pain and emotional processing.

Prestimulus dynamics blend with the stimulus in neural variability quenching.

Neural responses to the same stimulus show significant variability over trials, with this variability typically reduced (quenched) after a stimulus is presented. This trial-to-trial variability (TTV) has been much studied, however how this neural variability quenching is influenced by the ongoing dynamics of the prestimulus period is unknown. Utilizing a human intracranial stereo-electroencephalography (sEEG) data set, we investigate how prestimulus dynamics, as operationalized by standard deviation (SD), shapes poststimulus activity through trial-to-trial variability (TTV). We first observed greater poststimulus variability quenching in those real trials exhibiting high prestimulus variability as observed in all frequency bands. Next, we found that the relative effect of the stimulus was higher in the later (300-600ms) than the earlier (0-300ms) poststimulus period. Lastly, we replicate our findings in a separate EEG dataset and extend them by finding that trials with high prestimulus variability in the theta and alpha bands had faster reaction times. Together, our results demonstrate that stimulus-related activity, including its variability, is a blend of two factors: 1) the effects of the external stimulus itself, and 2) the effects of the ongoing dynamics spilling over from the prestimulus period - the state at stimulus onset - with the second dwarfing the influence of the first.

Are intrinsic neural timescales related to sensory processing? Evidence from abnormal behavioral states.

The brain exhibits a complex temporal structure which translates into a hierarchy of distinct neural timescales. An open question is how these intrinsic timescales are related to sensory or motor information processing and whether these dynamics have common patterns in different behavioral states. We address these questions by investigating the brain's intrinsic timescales in healthy controls, motor (amyotrophic lateral sclerosis, locked-in syndrome), sensory (anesthesia, unresponsive wakefulness syndrome), and progressive reduction of sensory processing (from awake states over N1, N2, N3). We employed a combination of measures from EEG resting-state data: auto-correlation window (ACW), power spectral density (PSD), and power-law exponent (PLE). Prolonged neural timescales accompanied by a shift towards slower frequencies were observed in the conditions with sensory deficits, but not in conditions with motor deficits. Our results establish that the spontaneous activity's intrinsic neural timescale is related to the neural capacity that specifically supports sensory rather than motor information processing in the healthy brain.

Occupational contact dermatitis: Return to work using a multidisciplinary clinic model.

BACKGROUND: Occupational contact dermatitis often results in work disruption. Return-to-work (RTW) is an important outcome. OBJECTIVE: The objective of this study was to determine RTW outcomes and factors associated with such outcomes using a multidisciplinary clinic model. METHODS: Chart abstraction was performed for 194 workers who received RTW assistance over a 6-year period. Elements abstracted included demographic and diagnostic information and information about the RTW program including principles, program components, barriers, and facilitators. RESULTS: Of the 902 workers seen for dermatologic assessment, 194 received RTW assistance. At initial assessment, 37% were not working because of their skin disease, and at follow-up, 7% were not working because of their skin disease. The RTW plan components included a graduated or trial of RTW, specific recommendations for avoiding exposure, personal protective equipment, skin management, and ongoing skin monitoring. Principles associated with successful RTW included good communication and the availability of modified work and a worker adherence to the plan. Barriers included lack of modified work, unresponsive employers, and ongoing skin problems. CONCLUSIONS: Specific approaches are important to identify if RTW is to be successful for workers with occupational contact dermatitis.

Netrin-1 in Glioblastoma Neovascularization: The New Partner in Crime?

Glioblastoma (GBM) is the most aggressive and common primary tumor of the central nervous system. It is characterized by having an infiltrating growth and by the presence of an excessive and aberrant vasculature. Some of the mechanisms that promote this neovascularization are angiogenesis and the transdifferentiation of tumor cells into endothelial cells or pericytes. In all these processes, the release of extracellular microvesicles by tumor cells plays an important role. Tumor cell-derived extracellular microvesicles contain pro-angiogenic molecules such as VEGF, which promote the formation of blood vessels and the recruitment of pericytes that reinforce these structures. The present study summarizes and discusses recent data from different investigations suggesting that Netrin-1, a highly versatile protein recently postulated as a non-canonical angiogenic ligand, could participate in the promotion of neovascularization processes in GBM. The relevance of determining the angiogenic signaling pathways associated with the interaction of Netrin-1 with its receptors is posed. Furthermore, we speculate that this molecule could form part of the microvesicles that favor abnormal tumor vasculature. Based on the studies presented, this review proposes Netrin-1 as a novel biomarker for GBM progression and vascularization.

The Embryonic Key Pluripotent Factor NANOG Mediates Glioblastoma Cell Migration via the SDF1/CXCR4 Pathway.

NANOG is a key transcription factor required for maintaining pluripotency of embryonic stem cells. Elevated NANOG expression levels have been reported in many types of human cancers, including lung, oral, prostate, stomach, breast, and brain. Several studies reported the correlation between NANOG expression and tumor metastasis, revealing itself as a powerful biomarker of poor prognosis. However, how NANOG regulates tumor progression is still not known. We previously showed in medaka fish that Nanog regulates primordial germ cell migration through Cxcr4b, a chemokine receptor known for its ability to promote migration and metastasis in human cancers. Therefore, we investigated the role of human NANOG in CXCR4-mediated cancer cell migration. Of note, we found that NANOG regulatory elements in the CXCR4 promoter are functionally conserved in medaka fish and humans, suggesting an evolutionary conserved regulatory axis. Moreover, CXCR4 expression requires NANOG in human glioblastoma cells. In addition, transwell assays demonstrated that NANOG regulates cancer cell migration through the SDF1/CXCR4 pathway. Altogether, our results uncover NANOG-CXCR4 as a novel pathway controlling cellular migration and support Nanog as a potential therapeutic target in the treatment of Nanog-dependent tumor progression.